Overview

Brought to you by YData

Dataset statistics

Number of variables15
Number of observations9357
Missing cells0
Missing cells (%)0.0%
Duplicate rows3
Duplicate rows (%)< 0.1%
Total size in memory1.1 MiB
Average record size in memory120.0 B

Variable types

DateTime1
Unsupported1
Numeric13

Alerts

Dataset has 3 (< 0.1%) duplicate rowsDuplicates
AH is highly overall correlated with PT08.S4(NO2) and 1 other fieldsHigh correlation
C6H6(GT) is highly overall correlated with CO(GT) and 5 other fieldsHigh correlation
CO(GT) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
NO2(GT) is highly overall correlated with CO(GT) and 2 other fieldsHigh correlation
NOx(GT) is highly overall correlated with CO(GT) and 4 other fieldsHigh correlation
PT08.S1(CO) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
PT08.S2(NMHC) is highly overall correlated with C6H6(GT) and 5 other fieldsHigh correlation
PT08.S3(NOx) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
PT08.S4(NO2) is highly overall correlated with AH and 5 other fieldsHigh correlation
PT08.S5(O3) is highly overall correlated with C6H6(GT) and 6 other fieldsHigh correlation
T is highly overall correlated with AH and 1 other fieldsHigh correlation
Time is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2025-06-21 19:08:50.434939
Analysis finished2025-06-21 19:09:14.452683
Duration24.02 seconds
Software versionydata-profiling vv4.16.1
Download configurationconfig.json

Variables

Date
Date

Distinct391
Distinct (%)4.2%
Missing0
Missing (%)0.0%
Memory size73.2 KiB
Minimum2004-03-10 00:00:00
Maximum2005-04-04 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-06-21T19:09:14.576492image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:14.775773image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

Time
Unsupported

Rejected  Unsupported 

Missing0
Missing (%)0.0%
Memory size73.2 KiB

CO(GT)
Real number (ℝ)

High correlation 

Distinct97
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-34.207524
Minimum-200
Maximum11.9
Zeros0
Zeros (%)0.0%
Negative1683
Negative (%)18.0%
Memory size73.2 KiB
2025-06-21T19:09:14.933024image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q10.6
median1.5
Q32.6
95-th percentile4.7
Maximum11.9
Range211.9
Interquartile range (IQR)2

Descriptive statistics

Standard deviation77.65717
Coefficient of variation (CV)-2.2701781
Kurtosis0.77830552
Mean-34.207524
Median Absolute Deviation (MAD)1
Skewness-1.6661795
Sum-320079.8
Variance6030.6361
MonotonicityNot monotonic
2025-06-21T19:09:15.073193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1683
 
18.0%
1 305
 
3.3%
1.4 279
 
3.0%
1.6 275
 
2.9%
1.5 273
 
2.9%
1.1 262
 
2.8%
0.7 260
 
2.8%
1.7 258
 
2.8%
1.3 253
 
2.7%
0.8 251
 
2.7%
Other values (87) 5258
56.2%
ValueCountFrequency (%)
-200 1683
18.0%
0.1 33
 
0.4%
0.2 45
 
0.5%
0.3 98
 
1.0%
0.4 160
 
1.7%
0.5 217
 
2.3%
0.6 244
 
2.6%
0.7 260
 
2.8%
0.8 251
 
2.7%
0.9 248
 
2.7%
ValueCountFrequency (%)
11.9 1
< 0.1%
11.5 1
< 0.1%
10.2 2
< 0.1%
10.1 1
< 0.1%
9.9 1
< 0.1%
9.5 1
< 0.1%
9.4 1
< 0.1%
9.3 1
< 0.1%
9.2 1
< 0.1%
9.1 2
< 0.1%

PT08.S1(CO)
Real number (ℝ)

High correlation 

Distinct3246
Distinct (%)34.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1048.8697
Minimum-200
Maximum2039.75
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:15.218095image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile745.7
Q1921
median1052.5
Q31221.25
95-th percentile1501.55
Maximum2039.75
Range2239.75
Interquartile range (IQR)300.25

Descriptive statistics

Standard deviation329.81701
Coefficient of variation (CV)0.31444995
Kurtosis5.8355116
Mean1048.8697
Median Absolute Deviation (MAD)147.16667
Skewness-1.7211263
Sum9814273.3
Variance108779.26
MonotonicityNot monotonic
2025-06-21T19:09:15.378902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
1099.5 12
 
0.1%
954.25 12
 
0.1%
986.75 12
 
0.1%
988.25 11
 
0.1%
969 11
 
0.1%
888 11
 
0.1%
890.75 11
 
0.1%
925.75 11
 
0.1%
1009.25 11
 
0.1%
Other values (3236) 8889
95.0%
ValueCountFrequency (%)
-200 366
3.9%
647.25 1
 
< 0.1%
648.75 1
 
< 0.1%
654.75 1
 
< 0.1%
666.75 1
 
< 0.1%
667 1
 
< 0.1%
667.25 1
 
< 0.1%
669.25 1
 
< 0.1%
676.25 1
 
< 0.1%
677.5 1
 
< 0.1%
ValueCountFrequency (%)
2039.75 1
< 0.1%
2007.75 1
< 0.1%
1982.25 1
< 0.1%
1974.75 1
< 0.1%
1972.5 1
< 0.1%
1961.25 1
< 0.1%
1956 1
< 0.1%
1934 1
< 0.1%
1917.75 1
< 0.1%
1917 1
< 0.1%

NMHC(GT)
Real number (ℝ)

Distinct430
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-159.09009
Minimum-200
Maximum1189
Zeros0
Zeros (%)0.0%
Negative8443
Negative (%)90.2%
Memory size73.2 KiB
2025-06-21T19:09:15.522382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q1-200
median-200
Q3-200
95-th percentile144.2
Maximum1189
Range1389
Interquartile range (IQR)0

Descriptive statistics

Standard deviation139.78909
Coefficient of variation (CV)-0.87867881
Kurtosis18.863824
Mean-159.09009
Median Absolute Deviation (MAD)0
Skewness4.0757845
Sum-1488606
Variance19540.99
MonotonicityNot monotonic
2025-06-21T19:09:15.673803image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 8443
90.2%
66 14
 
0.1%
40 9
 
0.1%
29 9
 
0.1%
88 8
 
0.1%
93 8
 
0.1%
95 7
 
0.1%
84 7
 
0.1%
57 7
 
0.1%
55 7
 
0.1%
Other values (420) 838
 
9.0%
ValueCountFrequency (%)
-200 8443
90.2%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 1
 
< 0.1%
11 1
 
< 0.1%
14 2
 
< 0.1%
16 1
 
< 0.1%
17 4
 
< 0.1%
18 2
 
< 0.1%
ValueCountFrequency (%)
1189 1
< 0.1%
1129 1
< 0.1%
1084 1
< 0.1%
1042 1
< 0.1%
974 1
< 0.1%
926 1
< 0.1%
899 1
< 0.1%
880 1
< 0.1%
872 1
< 0.1%
840 1
< 0.1%

C6H6(GT)
Real number (ℝ)

High correlation 

Distinct3773
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.8655759
Minimum-200
Maximum63.741476
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:15.878260image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile0.73622475
Q14.004958
median7.8866528
Q313.636091
95-th percentile24.432425
Maximum63.741476
Range263.74148
Interquartile range (IQR)9.6311332

Descriptive statistics

Standard deviation41.380154
Coefficient of variation (CV)22.1809
Kurtosis19.188714
Mean1.8655759
Median Absolute Deviation (MAD)4.4659639
Skewness-4.5087745
Sum17456.194
Variance1712.3171
MonotonicityNot monotonic
2025-06-21T19:09:16.044921image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
6.849891944 13
 
0.1%
4.04571731 9
 
0.1%
5.560495658 9
 
0.1%
6.810174913 9
 
0.1%
10.18426339 9
 
0.1%
5.544912139 8
 
0.1%
6.291887126 8
 
0.1%
5.738409862 8
 
0.1%
5.101134318 8
 
0.1%
Other values (3763) 8910
95.2%
ValueCountFrequency (%)
-200 366
3.9%
0.1490477388 2
 
< 0.1%
0.1649456884 1
 
< 0.1%
0.1719683734 1
 
< 0.1%
0.1815254092 2
 
< 0.1%
0.2127981659 1
 
< 0.1%
0.2241305792 1
 
< 0.1%
0.2406875551 1
 
< 0.1%
0.2420520143 1
 
< 0.1%
0.2671717608 1
 
< 0.1%
ValueCountFrequency (%)
63.74147645 1
< 0.1%
52.05406416 1
< 0.1%
50.77953259 1
< 0.1%
50.67281895 1
< 0.1%
50.63282602 1
< 0.1%
49.49209269 1
< 0.1%
49.4393052 1
< 0.1%
48.21877473 1
< 0.1%
47.67183594 1
< 0.1%
47.4771456 1
< 0.1%

PT08.S2(NMHC)
Real number (ℝ)

High correlation 

Distinct3773
Distinct (%)40.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean894.47596
Minimum-200
Maximum2214
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:16.218807image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile470.95
Q1711
median894.5
Q31104.75
95-th percentile1414.65
Maximum2214
Range2414
Interquartile range (IQR)393.75

Descriptive statistics

Standard deviation342.3159
Coefficient of variation (CV)0.38269995
Kurtosis2.3694254
Mean894.47596
Median Absolute Deviation (MAD)194.5
Skewness-0.79315296
Sum8369611.6
Variance117180.18
MonotonicityNot monotonic
2025-06-21T19:09:16.379033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
850.25 13
 
0.1%
713.25 9
 
0.1%
791 9
 
0.1%
848.5 9
 
0.1%
984.5 9
 
0.1%
790.25 8
 
0.1%
825.25 8
 
0.1%
799.5 8
 
0.1%
768.5 8
 
0.1%
Other values (3763) 8910
95.2%
ValueCountFrequency (%)
-200 366
3.9%
383.25 2
 
< 0.1%
386.75 1
 
< 0.1%
388.25 1
 
< 0.1%
390.25 2
 
< 0.1%
396.5 1
 
< 0.1%
398.6666667 1
 
< 0.1%
401.75 1
 
< 0.1%
402 1
 
< 0.1%
406.5 1
 
< 0.1%
ValueCountFrequency (%)
2214 1
< 0.1%
2006.75 1
< 0.1%
1983 1
< 0.1%
1981 1
< 0.1%
1980.25 1
< 0.1%
1958.75 1
< 0.1%
1957.75 1
< 0.1%
1934.5 1
< 0.1%
1924 1
< 0.1%
1920.25 1
< 0.1%

NOx(GT)
Real number (ℝ)

High correlation 

Distinct2467
Distinct (%)26.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean168.6042
Minimum-200
Maximum1479
Zeros0
Zeros (%)0.0%
Negative1639
Negative (%)17.5%
Memory size73.2 KiB
2025-06-21T19:09:16.524669image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q150
median141
Q3284.2
95-th percentile652.96
Maximum1479
Range1679
Interquartile range (IQR)234.2

Descriptive statistics

Standard deviation257.42456
Coefficient of variation (CV)1.526798
Kurtosis1.5055659
Mean168.6042
Median Absolute Deviation (MAD)108.8
Skewness0.82525519
Sum1577629.5
Variance66267.405
MonotonicityNot monotonic
2025-06-21T19:09:16.676582image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1639
 
17.5%
65 37
 
0.4%
89 36
 
0.4%
41 36
 
0.4%
57 32
 
0.3%
46 31
 
0.3%
61 31
 
0.3%
51 31
 
0.3%
111 30
 
0.3%
72 30
 
0.3%
Other values (2457) 7424
79.3%
ValueCountFrequency (%)
-200 1639
17.5%
2 1
 
< 0.1%
4 1
 
< 0.1%
6 1
 
< 0.1%
7 1
 
< 0.1%
8 1
 
< 0.1%
9 1
 
< 0.1%
10 3
 
< 0.1%
11 4
 
< 0.1%
12 4
 
< 0.1%
ValueCountFrequency (%)
1479 1
< 0.1%
1389 2
< 0.1%
1369 1
< 0.1%
1358 1
< 0.1%
1345 1
< 0.1%
1310 1
< 0.1%
1301 1
< 0.1%
1290 1
< 0.1%
1253 1
< 0.1%
1247 1
< 0.1%

PT08.S3(NOx)
Real number (ℝ)

High correlation 

Distinct3519
Distinct (%)37.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean794.87233
Minimum-200
Maximum2682.75
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:16.823105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile409.95
Q1637
median794.25
Q3960.25
95-th percentile1281.1
Maximum2682.75
Range2882.75
Interquartile range (IQR)323.25

Descriptive statistics

Standard deviation321.97703
Coefficient of variation (CV)0.4050676
Kurtosis3.1042149
Mean794.87233
Median Absolute Deviation (MAD)161
Skewness-0.38446386
Sum7437620.4
Variance103669.21
MonotonicityNot monotonic
2025-06-21T19:09:16.991814image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
829.5 11
 
0.1%
866.25 10
 
0.1%
683.25 10
 
0.1%
844.5 9
 
0.1%
696.75 9
 
0.1%
815.5 9
 
0.1%
732.5 9
 
0.1%
767 9
 
0.1%
793 9
 
0.1%
Other values (3509) 8906
95.2%
ValueCountFrequency (%)
-200 366
3.9%
322 1
 
< 0.1%
324.5 1
 
< 0.1%
325.25 1
 
< 0.1%
328 1
 
< 0.1%
329.75 2
 
< 0.1%
333.5 1
 
< 0.1%
334.5 1
 
< 0.1%
339.5 1
 
< 0.1%
340 1
 
< 0.1%
ValueCountFrequency (%)
2682.75 1
< 0.1%
2559.25 1
< 0.1%
2541.5 1
< 0.1%
2330.75 1
< 0.1%
2327 1
< 0.1%
2317.75 1
< 0.1%
2294 1
< 0.1%
2121.25 1
< 0.1%
2095.25 1
< 0.1%
2094.75 1
< 0.1%

NO2(GT)
Real number (ℝ)

High correlation 

Distinct1420
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.135898
Minimum-200
Maximum339.7
Zeros0
Zeros (%)0.0%
Negative1642
Negative (%)17.5%
Memory size73.2 KiB
2025-06-21T19:09:17.126388image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile-200
Q153
median96
Q3133
95-th percentile194
Maximum339.7
Range539.7
Interquartile range (IQR)80

Descriptive statistics

Standard deviation126.93143
Coefficient of variation (CV)2.1833571
Kurtosis0.27571718
Mean58.135898
Median Absolute Deviation (MAD)40
Skewness-1.2257893
Sum543977.6
Variance16111.587
MonotonicityNot monotonic
2025-06-21T19:09:17.281527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 1642
 
17.5%
97 68
 
0.7%
95 66
 
0.7%
101 65
 
0.7%
114 63
 
0.7%
68 63
 
0.7%
99 62
 
0.7%
96 62
 
0.7%
107 61
 
0.7%
119 61
 
0.7%
Other values (1410) 7144
76.3%
ValueCountFrequency (%)
-200 1642
17.5%
2 1
 
< 0.1%
3 1
 
< 0.1%
5 2
 
< 0.1%
7 1
 
< 0.1%
8 2
 
< 0.1%
9 2
 
< 0.1%
11 2
 
< 0.1%
12 2
 
< 0.1%
13 1
 
< 0.1%
ValueCountFrequency (%)
339.7 1
< 0.1%
332.6 1
< 0.1%
325.9 1
< 0.1%
321.6 1
< 0.1%
312.4 1
< 0.1%
310.1 1
< 0.1%
309.2 1
< 0.1%
306.4 1
< 0.1%
301.1 1
< 0.1%
295.6 1
< 0.1%

PT08.S4(NO2)
Real number (ℝ)

High correlation 

Distinct4408
Distinct (%)47.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1391.3633
Minimum-200
Maximum2775
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:17.429508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile757.1
Q11184.75
median1445.5
Q31662
95-th percentile2020.3
Maximum2775
Range2975
Interquartile range (IQR)477.25

Descriptive statistics

Standard deviation467.19238
Coefficient of variation (CV)0.3357803
Kurtosis3.2663876
Mean1391.3633
Median Absolute Deviation (MAD)235.5
Skewness-1.2439438
Sum13018986
Variance218268.72
MonotonicityNot monotonic
2025-06-21T19:09:17.561674image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
1490 10
 
0.1%
1363 9
 
0.1%
1488.25 8
 
0.1%
1538.5 8
 
0.1%
1623 8
 
0.1%
1479.25 8
 
0.1%
1430 8
 
0.1%
1400 8
 
0.1%
1533.5 8
 
0.1%
Other values (4398) 8916
95.3%
ValueCountFrequency (%)
-200 366
3.9%
551 1
 
< 0.1%
559.25 1
 
< 0.1%
560.5 1
 
< 0.1%
579 1
 
< 0.1%
601 1
 
< 0.1%
601.75 1
 
< 0.1%
604.75 1
 
< 0.1%
621.25 1
 
< 0.1%
637 1
 
< 0.1%
ValueCountFrequency (%)
2775 1
< 0.1%
2746 1
< 0.1%
2690.5 1
< 0.1%
2684 1
< 0.1%
2679 1
< 0.1%
2666.5 1
< 0.1%
2665.25 1
< 0.1%
2662 1
< 0.1%
2643 1
< 0.1%
2642.75 1
< 0.1%

PT08.S5(O3)
Real number (ℝ)

High correlation 

Distinct4679
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean974.95153
Minimum-200
Maximum2522.75
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:17.705250image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile347.75
Q1699.75
median942
Q31255.25
95-th percentile1749.65
Maximum2522.75
Range2722.75
Interquartile range (IQR)555.5

Descriptive statistics

Standard deviation456.92273
Coefficient of variation (CV)0.46866199
Kurtosis0.63795655
Mean974.95153
Median Absolute Deviation (MAD)272.25
Skewness-0.034500045
Sum9122621.5
Variance208778.38
MonotonicityNot monotonic
2025-06-21T19:09:17.864929image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
825.75 10
 
0.1%
835.5 8
 
0.1%
1049.75 8
 
0.1%
779 8
 
0.1%
1023.5 8
 
0.1%
904.5 8
 
0.1%
776.5 7
 
0.1%
1001.25 7
 
0.1%
925.75 7
 
0.1%
Other values (4669) 8920
95.3%
ValueCountFrequency (%)
-200 366
3.9%
221 1
 
< 0.1%
224.75 1
 
< 0.1%
226.5 1
 
< 0.1%
232 1
 
< 0.1%
252 1
 
< 0.1%
252.5 1
 
< 0.1%
257 1
 
< 0.1%
260.5 1
 
< 0.1%
261 1
 
< 0.1%
ValueCountFrequency (%)
2522.75 1
< 0.1%
2522.25 1
< 0.1%
2519.25 1
< 0.1%
2515.25 1
< 0.1%
2493.5 1
< 0.1%
2480.25 1
< 0.1%
2474.75 1
< 0.1%
2465 1
< 0.1%
2452 1
< 0.1%
2433.5 1
< 0.1%

T
Real number (ℝ)

High correlation 

Distinct3368
Distinct (%)36.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.7765995
Minimum-200
Maximum44.6
Zeros0
Zeros (%)0.0%
Negative380
Negative (%)4.1%
Memory size73.2 KiB
2025-06-21T19:09:18.063284image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile2.5
Q110.95
median17.2
Q324.075
95-th percentile34.325
Maximum44.6
Range244.6
Interquartile range (IQR)13.125

Descriptive statistics

Standard deviation43.203438
Coefficient of variation (CV)4.4190659
Kurtosis18.774475
Mean9.7765995
Median Absolute Deviation (MAD)6.5500004
Skewness-4.445411
Sum91479.642
Variance1866.537
MonotonicityNot monotonic
2025-06-21T19:09:18.212156image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
23.04999971 15
 
0.2%
15.05000019 15
 
0.2%
20.80000019 13
 
0.1%
24 13
 
0.1%
14.57500005 12
 
0.1%
17.57499981 11
 
0.1%
21.3499999 11
 
0.1%
19.2750001 11
 
0.1%
20.1500001 11
 
0.1%
Other values (3358) 8879
94.9%
ValueCountFrequency (%)
-200 366
3.9%
-1.899999976 1
 
< 0.1%
-1.374999989 1
 
< 0.1%
-1.274999991 2
 
< 0.1%
-1.199999988 1
 
< 0.1%
-1.124999985 1
 
< 0.1%
-0.5500000194 2
 
< 0.1%
-0.4749999791 1
 
< 0.1%
-0.2500000056 1
 
< 0.1%
-0.1500000022 1
 
< 0.1%
ValueCountFrequency (%)
44.60000038 1
< 0.1%
44.34999943 1
< 0.1%
43.42499924 1
< 0.1%
43.12500095 1
< 0.1%
42.82499981 1
< 0.1%
42.79999924 1
< 0.1%
42.77500057 1
< 0.1%
42.67499924 1
< 0.1%
42.625 1
< 0.1%
42.5 1
< 0.1%

RH
Real number (ℝ)

Distinct4903
Distinct (%)52.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.483611
Minimum-200
Maximum88.725
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:18.351204image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile15.025
Q134.05
median48.55
Q361.875
95-th percentile77.625
Maximum88.725
Range288.725
Interquartile range (IQR)27.825

Descriptive statistics

Standard deviation51.215645
Coefficient of variation (CV)1.2971368
Kurtosis15.764326
Mean39.483611
Median Absolute Deviation (MAD)13.924999
Skewness-3.9324398
Sum369448.15
Variance2623.0423
MonotonicityNot monotonic
2025-06-21T19:09:18.502333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
47.75 11
 
0.1%
51.44999981 9
 
0.1%
54.5 8
 
0.1%
50.10000038 8
 
0.1%
55.94999981 8
 
0.1%
57.92500019 8
 
0.1%
49.67500019 8
 
0.1%
50.125 7
 
0.1%
51.52499962 7
 
0.1%
Other values (4893) 8917
95.3%
ValueCountFrequency (%)
-200 366
3.9%
9.175000191 1
 
< 0.1%
9.224999905 1
 
< 0.1%
9.300000191 1
 
< 0.1%
9.599999905 1
 
< 0.1%
9.799999952 1
 
< 0.1%
9.875000238 1
 
< 0.1%
9.900000095 1
 
< 0.1%
9.950000048 1
 
< 0.1%
9.974999905 1
 
< 0.1%
ValueCountFrequency (%)
88.72500038 1
< 0.1%
87.17499924 1
< 0.1%
87.07499886 1
< 0.1%
86.95000076 1
< 0.1%
86.62500191 1
< 0.1%
86.55000114 1
< 0.1%
86.52500153 1
< 0.1%
86.47500038 1
< 0.1%
86.00000191 1
< 0.1%
85.69999886 1
< 0.1%

AH
Real number (ℝ)

High correlation 

Distinct8988
Distinct (%)96.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean-6.8376037
Minimum-200
Maximum2.2310357
Zeros0
Zeros (%)0.0%
Negative366
Negative (%)3.9%
Memory size73.2 KiB
2025-06-21T19:09:18.641485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum-200
5-th percentile0.29509596
Q10.69227535
median0.9768229
Q31.2962231
95-th percentile1.7204083
Maximum2.2310357
Range202.23104
Interquartile range (IQR)0.60394779

Descriptive statistics

Standard deviation38.97667
Coefficient of variation (CV)-5.7003406
Kurtosis20.613092
Mean-6.8376037
Median Absolute Deviation (MAD)0.30220562
Skewness-4.7545703
Sum-63979.458
Variance1519.1808
MonotonicityNot monotonic
2025-06-21T19:09:19.227680image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-200 366
 
3.9%
0.7797699428 2
 
< 0.1%
0.7058010096 2
 
< 0.1%
1.471325566 2
 
< 0.1%
1.320841244 2
 
< 0.1%
0.4550786446 1
 
< 0.1%
0.4244852497 1
 
< 0.1%
0.3686173985 1
 
< 0.1%
0.3213631544 1
 
< 0.1%
0.3645814842 1
 
< 0.1%
Other values (8978) 8978
95.9%
ValueCountFrequency (%)
-200 366
3.9%
0.184679021 1
 
< 0.1%
0.1861794399 1
 
< 0.1%
0.1909612085 1
 
< 0.1%
0.1974686974 1
 
< 0.1%
0.1987566874 1
 
< 0.1%
0.2028527693 1
 
< 0.1%
0.2031033497 1
 
< 0.1%
0.2061708872 1
 
< 0.1%
0.2085747799 1
 
< 0.1%
ValueCountFrequency (%)
2.231035716 1
< 0.1%
2.180639319 1
< 0.1%
2.176616312 1
< 0.1%
2.171932117 1
< 0.1%
2.139495892 1
< 0.1%
2.136178693 1
< 0.1%
2.124690971 1
< 0.1%
2.119450226 1
< 0.1%
2.117033465 1
< 0.1%
2.116387171 1
< 0.1%

Interactions

2025-06-21T19:09:11.362478image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.197863image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.857610image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.296237image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.078620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.555426image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:59.657186image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.743641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.226381image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.737433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.572199image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.215283image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.764098image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.056945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.312654image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.955120image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.401887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.174678image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.662335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:59.854233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.854548image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.331271image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.858844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.797346image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.321233image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.864266image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.238887image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.410629image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.051047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.513701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.276433image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.804211image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.007716image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.956540image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.435991image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.263547image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.040415image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.425825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.965549image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.415138image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.518831image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.156616image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.679154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.414410image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.911639image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.163726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.077176image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.545053image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.378968image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.155004image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.536581image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.100315image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.566901image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.639461image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.269224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.795021image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.518598image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.018810image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.332325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.185966image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.658185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.480643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.261231image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.650583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.212392image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.716841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:51.776290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.370480image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.906821image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.623124image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.114242image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.493436image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.292878image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.823808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.586335image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.361727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.795191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.324174image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:12.893996image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.054980image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.482496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.021914image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.734313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.220169image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.695504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.407118image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.931191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.710290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.468736image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.910527image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.438511image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.070926image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.175184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.600529image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.355011image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.883780image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.329694image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:00.923429image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.516459image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.038712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.871916image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.565453image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.032535image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.551871image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.257761image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.290333image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.704630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.462739image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:56.985620image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.438063image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.087105image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.626354image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.156060image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:05.979215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.668978image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.137471image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.701221image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.448570image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.389711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.860816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.576954image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.097673image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.612485image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.199564image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.790081image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.264603image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.085945image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.766509image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.254820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.814179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.639647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.493590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:53.961808image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.689905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.208984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:58.837618image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.316129image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:02.893042image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.370154image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.196422image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.868391image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.364888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:10.920215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.830664image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.598984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.061819image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.809023image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.315949image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:59.010313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.424447image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.003992image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.471998image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.308000image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:07.989600image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.463523image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:11.040409image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:13.943293image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:52.708435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:54.166774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:55.964325image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:57.434338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:08:59.181047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:01.539825image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:03.114041image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:04.577020image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:06.421341image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:08.103734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:09.603099image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-06-21T19:09:11.195782image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-06-21T19:09:19.351230image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AHC6H6(GT)CO(GT)NMHC(GT)NO2(GT)NOx(GT)PT08.S1(CO)PT08.S2(NMHC)PT08.S3(NOx)PT08.S4(NO2)PT08.S5(O3)RHT
AH1.0000.283-0.114-0.157-0.330-0.2430.2350.283-0.0800.6850.1870.2510.735
C6H6(GT)0.2831.0000.5900.0280.4570.4800.9021.000-0.6420.7770.8880.0040.357
CO(GT)-0.1140.5901.0000.1360.7710.8130.5840.590-0.5800.3050.576-0.043-0.071
NMHC(GT)-0.1570.0280.1361.0000.022-0.0380.1320.0280.1610.1200.0250.011-0.096
NO2(GT)-0.3300.4570.7710.0221.0000.9060.4760.457-0.5220.0610.498-0.134-0.203
NOx(GT)-0.2430.4800.813-0.0380.9061.0000.5070.480-0.5810.0660.5510.058-0.263
PT08.S1(CO)0.2350.9020.5840.1320.4760.5071.0000.902-0.6450.6860.9060.1950.185
PT08.S2(NMHC)0.2831.0000.5900.0280.4570.4800.9021.000-0.6420.7770.8880.0040.357
PT08.S3(NOx)-0.080-0.642-0.5800.161-0.522-0.581-0.645-0.6421.000-0.363-0.6520.0380.008
PT08.S4(NO2)0.6850.7770.3050.1200.0610.0660.6860.777-0.3631.0000.6100.0540.658
PT08.S5(O3)0.1870.8880.5760.0250.4980.5510.9060.888-0.6520.6101.0000.2260.111
RH0.2510.004-0.0430.011-0.1340.0580.1950.0040.0380.0540.2261.000-0.369
T0.7350.357-0.071-0.096-0.203-0.2630.1850.3570.0080.6580.111-0.3691.000

Missing values

2025-06-21T19:09:14.130506image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-06-21T19:09:14.308870image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

DateTimeCO(GT)PT08.S1(CO)NMHC(GT)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
02004-03-1018:00:002.61360.0015011.8817231045.50166.01056.25113.01692.001267.5013.60048.8750010.757754
12004-03-1019:00:002.01292.251129.397165954.75103.01173.7592.01558.75972.2513.30047.7000000.725487
22004-03-1020:00:002.21402.00888.997817939.25131.01140.00114.01554.501074.0011.90053.9750000.750239
32004-03-1021:00:002.21375.50809.228796948.25172.01092.00122.01583.751203.2511.00060.0000000.786713
42004-03-1022:00:001.61272.25516.518224835.50131.01205.00116.01490.001110.0011.15059.5750010.788794
52004-03-1023:00:001.21197.00384.741012750.2589.01336.5096.01393.00949.2511.17559.1750000.784772
62004-03-1100:00:001.21185.00313.624399689.5062.01461.7577.01332.75732.5011.32556.7750000.760312
72004-03-1101:00:001.01136.25313.326677672.0062.01453.2576.01332.75729.5010.67560.0000000.770238
82004-03-1102:00:000.91094.00242.339416608.5045.01579.0060.01276.00619.5010.65059.6749990.764819
92004-03-1103:00:000.61009.75191.696658560.75-200.01705.00-200.01234.75501.2510.25060.2000010.751657
DateTimeCO(GT)PT08.S1(CO)NMHC(GT)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH
93472005-04-0405:00:000.5888.25-2001.307608528.0076.51076.5053.1987.00577.5010.40000059.8750000.754964
93482005-04-0406:00:001.11030.50-2004.359341730.25182.2760.0093.01129.00905.009.55000063.1500000.753129
93492005-04-0407:00:004.01383.50-20017.3642401220.75593.7470.25154.61600.001457.259.67500061.9249990.744608
93502005-04-0408:00:005.01446.00-20022.3932331361.50586.2414.75173.61776.501704.5013.55000048.8750000.755337
93512005-04-0409:00:003.91296.50-20013.5523931102.00522.7506.75186.51375.251582.5018.15000136.2750010.748652
93522005-04-0410:00:003.11314.25-20013.5296051101.25471.7538.50189.81374.251728.5021.85000029.2500000.756824
93532005-04-0411:00:002.41162.50-20011.3551571027.00353.3603.75179.21263.501269.0024.32500023.7250000.711864
93542005-04-0412:00:002.41142.00-20012.3745381062.50293.0603.25174.71240.751092.0026.90000018.3500000.640649
93552005-04-0413:00:002.11002.50-2009.547187960.50234.5701.50155.71041.00769.7528.32500013.5500000.513866
93562005-04-0414:00:002.21070.75-20011.9320601047.25265.2654.00167.71128.50816.0028.50000013.1250000.502804

Duplicate rows

Most frequently occurring

DateCO(GT)PT08.S1(CO)NMHC(GT)C6H6(GT)PT08.S2(NMHC)NOx(GT)PT08.S3(NOx)NO2(GT)PT08.S4(NO2)PT08.S5(O3)TRHAH# duplicates
22004-09-08-200.0-200.0-200-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.016
12004-05-26-200.0-200.0-200-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.09
02004-05-25-200.0-200.0-200-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.0-200.05